[PDF] Top 20 Learning to Rank for Plausible Plausibility
Has 10000 "Learning to Rank for Plausible Plausibility" found on our website. Below are the top 20 most common "Learning to Rank for Plausible Plausibility".
Learning to Rank for Plausible Plausibility
... Under the Johns Hopkins Ordinal Common- sense Inference (JOCI) dataset (Zhang et al., 2017), instead of selecting which hypothesis is the most plausible, a model is expected to directly assign ordinal 5-level ... See full document
6
Entity attribute ranking using learning to rank
... Commercial search systems have recently begun using entity cards to support their ranked results lists. In this work, we propose an auto- mated method for entity card building. We model this problem as a learning ... See full document
6
Is Learning to Rank Worth it? A Statistical Analysis of Learning to Rank Methods in the LETOR Benchmarks
... The Learning to Rank (L2R) research field has experienced a fast paced growth over the last few years, with a wide variety of benchmark datasets and baselines available for ... See full document
10
Scaling Learning to Rank to Big Data: Using MapReduce to parallelise Learning to Rank
... of Learning to Rank methods has on the speed-up that can be achieved by parallelising the methods with the MapRe- duce model is still to be ...a Learning to Rank algorithm basically turns it ... See full document
125
Optimized Online Rank Learning for Machine Translation
... We compared four algorithms, MERT, PRO, MIRA and our proposed online settings, online rank optimization (ORO). Note that ORO without our op- timization methods in Section 4 is essentially the same as Pegasos, but ... See full document
10
ES Rank: evolution strategy learning to rank approach
... Moreover, learning models such as Okapi-BM25 and language models rely con- siderably on the relevance judgment in order to achieve good retrieval results [11, 25, ...machine learning and computational ... See full document
7
Learning to Rank using Query-Level Rules
... to rank offer substantial improvements in enough situations to be regarded as a relevant advance for applications that depend on ...this learning task is to assume the availability of examples ...which ... See full document
15
Learning to Rank Lexical Substitutions
... For each sentence in each dataset, the annotators provided as many substitutions for the target word as they found appropriate in the context. Each sub- stitution is then labeled by the number of annotators who listed ... See full document
7
Cost-Sensitive Learning to Rank
... could rank instances from highest predicted risk to lowest predicted ...applying Learning to Rank over Regression can require IR-only assumptions ...not rank well: consider the performance of ... See full document
8
Online Learning to Rank with Top-k Feedback
... on learning an optimal ranking of a subset of items, to be presented to an user, with performance judged by a simple 0-1 ...efficient learning is possible with the highly restricted feedback ... See full document
50
An evolutionary strategy with machine learning for learning to rank in information retrieval
... IESR- Rank uses linear regression and IESVM-Rank uses support vector machine for the initializa- tion ...IESR- Rank achieves the overall best ...Reciprocal Rank (RR@10) and Nor- malized ... See full document
19
Learning to Rank Relevant Files for Bug Reports Using Domain knowledge, Replication and Extension of a Learning-to-Rank Approach
... A similar methodology explained in [12] was applied for text pre-processing. In order for the bug reports and source code files to be converted into vectors of term weights, first they need to be preprocessed and ... See full document
53
Probabilistic preference learning with the Mallows rank model
... Consider a situation in which the assessors have expressed their preferences on a collection of items, by performing only partial rankings. Or, suppose that they have been asked to respond to some queries containing ... See full document
49
An Empirical Study on Learning to Rank of Tweets
... In this paper, we study three types of tweet features and propose a tweet ranking strategy by applying learning to rank algorithm. We find a set of most effective features for tweet ranking. The results of ... See full document
9
Learning to Rank Semantic Coherence for Topic Segmentation
... Topic segmentation plays an important role for discourse parsing and information retrieval. Due to the absence of train- ing data, previous work mainly adopts un- supervised methods to rank semantic co- herence ... See full document
5
Answering questions by learning to rank Learning to rank by answering questions
... In order to semantically discern relevant and irrelevant documents for a given question, we are designing a set of discriminators, each receiving a tuple (question, candidate answer, and document) and returning a ... See full document
10
Cross Lingual Learning to Rank with Shared Representations
... Cross-lingual information retrieval (CLIR) is a document retrieval task where the docu- ments are written in a language different from that of the user’s query. This is a chal- lenging problem for data-driven approaches ... See full document
6
Discovery of Ranking Fraud Using Evidence Aggregation Approach for Mobile Apps
... Unsupervised rank aggregation with distance-based models which needs to incorporate the arrangement of rankings regularly manages collecting and it just comes up when a specific positioned information is ... See full document
6
Invariant object recognition : biologically plausible and machine learning approaches
... biological plausibility of two models that purport to be bio- logically plausible or at the very least biologically ...biologically plausible they are, by comparing them to the expected responses of ... See full document
143
Interpolated PLSI for Learning Plausible Verb Arguments
... These words are important to our purposes, because filtering them out would prevent us to generalizing rare words for measuring their plausibility. The iPLSI (interpolated PLSI) algorithm proposed here deals with ... See full document
8
Related subjects